Business Intelligence

Technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.​

How the business intelligence process works?

business intelligence architecture includes more than just BI software. Business intelligence data is typically stored in a data warehouse built for an entire organization or in smaller data marts that hold subsets of business information for individual departments and business units, often with ties to an enterprise data warehouse. In addition, data lakes based on Hadoop clusters or other big data systems are increasingly used as repositories or landing pads for BI and analytics data, especially for log files, sensor data, text and other types of unstructured or semi structured data.

BI data can include historical information and real-time data gathered from source systems as it’s generated, enabling BI tools to support both strategic and tactical decision-making processes. Before it’s used in BI applications, raw data from different source systems generally must be integrated, consolidated and cleansed using data integration and data quality management tools to ensure that BI teams and business users are analyzing accurate and consistent information.

From there, the steps in the BI process include the following:

  • data preparation, in which data sets are organized and modeled for analysis;
  • analytical querying of the prepared data;
  • distribution of key performance indicators (KPIs) and other findings to business users; and
  • use of the information to help influence and drive business decisions.

Initially, BI tools were primarily used by BI and IT professionals who ran queries and produced dashboards and reports for business users. Increasingly, however, business analysts, executives and workers are using business intelligence platforms themselves, thanks to the development of self-service BI and data discovery tools. Self-service business intelligence environments enable business users to query BI data, create data visualizations and design dashboards on their own.

BI programs often incorporate forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical analysis and big data analytics. A common example is predictive modeling that enables what-if analysis of different business scenarios. In most cases, though, advanced analytics projects are conducted by separate teams of data scientists, statisticians, predictive modelers and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.

What is a business intelligence (BI)?

It is a tool for transforming data into information and then that information into knowledge using various methodologies. The objective of this process is to optimize the decision making of the company to the maximum since the acquired knowledge can be used to develop strategic or commercial plans.

Categories of Business Intelligence solutions

Data Management Tools: are those that allow debugging and standardizing the data, regardless of its origin, to its extraction, transformation, and transfer to a particular system.

Data Discovery Applications: These collect and evaluate the new information obtained through data mining. Once this process is done, you can use predictive analysis techniques to obtain future projections.

Reporting tools: with all the information collected and processed, these tools are presented graphically and intuitively, facilitating their use by the company.

What Business Intelligence is used for in companies

The benefits obtained by companies that use Business Intelligence range from the optimization of their resources to the improvement of the ability to make decisions, through the control that the company’s objectives are being met properly.

In this way, the BI becomes a strategic factor of the organization, offering answers to questions that may arise. Thanks to the treatment and analysis of the information, it is possible to control the finances and optimize the costs, as well as obtain an analysis of the client profile.

The competitive advantage it represents is evident: that information obtained will allow production planning or profitability that is more adjusted to reality.

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